Multi-resolution Modeling of Dynamic Signal Control on Urban Streets

Dynamic signal control provides significant benefits in terms of travel time, travel time reliability, and other performance measures of transportation systems. The goal of this research is to develop and evaluate a methodology to support the planning for operations of dynamic signal control utilizing a multi-resolution analysis approach. The multi-resolution analysis modeling combines analysis, modeling, and simulation (AMS) tools to support the assessment of the impacts of dynamic traffic signal control. Dynamic signal control strategies are effective in relieving congestions during non-typical days, such as those with high demands, incidents with different attributes, and adverse weather conditions. This research recognizes the need to model the impacts of dynamic signal controls for different days representing, different demand and incident levels. Methods are identified to calibrate the utilized tools for the patterns during different days based on demands and incident conditions utilizing combinations of real-world data with different levels of details. A significant challenge addressed in this study is to ensure that the mesoscopic simulation-based dynamic traffic assignment (DTA) models produces turning movement volumes at signalized intersections with sufficient accuracy for the purpose of the analysis. Although, an important aspect when modeling incident responsive signal control is to determine the capacity impacts of incidents considering the interaction between the drop in capacity below demands at the midblock urban street segment location and the upstream and downstream signalized intersection operations. A new model is developed to estimate the drop in capacity at the incident location by considering the downstream signal control queue spillback effects. A second model is developed to estimate the reduction in the upstream intersection capacity due to the drop in capacity at the midblock incident location as estimated by the first model. These developed models are used as part of a mesoscopic simulation-based DTA modeling to set the capacity during incident conditions, when such modeling is used to estimate the diversion during incidents. To supplement the DTA-based analysis, regression models are developed to estimate the diversion rate due to urban street incidents based on real-world data. These regression models are combined with the DTA model to estimate the volume at the incident location and alternative routes. The volumes with different demands and incident levels, resulting from DTA modeling are imported to a microscopic simulation model for more detailed analysis of dynamic signal control. The microscopic model shows that the implementation of special signal plans during incidents and different demand levels can improve mobility measures

Estimación de impactos de incidentes en el tiempo de viaje en la calle urbana en el caso de super saturación en las luces de traffic

Dynamic signal control strategies are effective in relieving congestions during nontypical days, such as those with high demands, incidents with different attributes, and adverse weather conditions. This research recognizes the need to model the impacts of dynamic signal controls for different days representing, different demand and incident levels. Methods are identified to calibrate the utilized tools for the patterns during different days based on demands and incident conditions utilizing combinations of real-world data with different levels of details. A significant challenge addressed in this study is to ensure that the mesoscopic simulation-based dynamic traffic assignment (DTA) models produces turning movement volumes at signalized intersections with sufficient accuracy for the purpose of the analysis. A new model is developed to estimate the drop in capacity at the incident location by considering the downstream signal control queue spillback effects. The developed capacity reduction models were used to estimate delay due to an urban street incident. The delay was calculated as a combination of the delay due to queuing on the incident link and the increase in upstream intersection control delays due the reduction in maximum throughputs resulting from queue spillback to the upstream intersection The HCS-based method estimated a reduction in delay resulting from the new signal timing plan to be around 3,404 vehicle-hours, whereas the VISSIM shows that the new signal timing saving in delay is 4,008 vehicle-hours. This confirms that the developed method and VISSIM estimation of the benefits are consistent.Las estrategias de control dinámico de la señal son efectivas para aliviar las congestiones durante los días no típicos, como aquellos con altas demandas, incidentes con diferentes atributos y condiciones climáticas adversas. Esta investigación reconoce la necesidad de modelar los impactos de los controles de señales dinámicas para diferentes días que representan diferentes niveles de demanda e incidentes. Los métodos se identifican para calibrar las herramientas utilizadas para los patrones durante diferentes días en función de las demandas y las condiciones del incidente utilizando combinaciones de datos del mundo real con diferentes niveles de detalles. Un desafío importante abordado en este estudio es garantizar que los modelos de asignación dinámica de tráfico (DTA) basados ​​en simulación mesoscópica produzcan volúmenes de movimiento de giro en intersecciones señalizadas con suficiente precisión para el propósito del análisis. Se desarrolla un nuevo modelo para estimar la caída de la capacidad en la ubicación del incidente considerando los efectos de derrame de la cola de control de señal aguas abajo. Los modelos de reducción de capacidad desarrollados se utilizaron para estimar el retraso debido a un incidente en una calle urbana. El retraso se calculó como una combinación del retraso debido a las colas en el enlace incidente y el aumento de los retrasos en el control de la intersección aguas arriba debido a la reducción en los rendimientos máximos resultantes del derrame de la cola a la intersección aguas arriba El método basado en HCS estimó una reducción en el retraso resultante del nuevo plan de temporización de la señal será de alrededor de 3.404 horas de vehículo, mientras que el VISSIM muestra que el nuevo ahorro de temporización de la señal con retraso es de 4.008 horas de vehículo. Esto confirma que el método desarrollado y la estimación VISSIM de los beneficios son consistentes

Multi-resolution Modeling of Dynamic Signal Control on Urban Streets

Dynamic signal control provides significant benefits in terms of travel time, travel time reliability, and other performance measures of transportation systems. The goal of this research is to develop and evaluate a methodology to support the planning for operations of dynamic signal control utilizing a multi-resolution analysis approach. The multi-resolution analysis modeling combines analysis, modeling, and simulation (AMS) tools to support the assessment of the impacts of dynamic traffic signal control. Dynamic signal control strategies are effective in relieving congestions during non-typical days, such as those with high demands, incidents with different attributes, and adverse weather conditions. This research recognizes the need to model the impacts of dynamic signal controls for different days representing, different demand and incident levels. Methods are identified to calibrate the utilized tools for the patterns during different days based on demands and incident conditions utilizing combinations of real-world data with different levels of details. A significant challenge addressed in this study is to ensure that the mesoscopic simulation-based dynamic traffic assignment (DTA) models produces turning movement volumes at signalized intersections with sufficient accuracy for the purpose of the analysis. Although, an important aspect when modeling incident responsive signal control is to determine the capacity impacts of incidents considering the interaction between the drop in capacity below demands at the midblock urban street segment location and the upstream and downstream signalized intersection operations. A new model is developed to estimate the drop in capacity at the incident location by considering the downstream signal control queue spillback effects. A second model is developed to estimate the reduction in the upstream intersection capacity due to the drop in capacity at the midblock incident location as estimated by the first model. These developed models are used as part of a mesoscopic simulation-based DTA modeling to set the capacity during incident conditions, when such modeling is used to estimate the diversion during incidents. To supplement the DTA-based analysis, regression models are developed to estimate the diversion rate due to urban street incidents based on real-world data. These regression models are combined with the DTA model to estimate the volume at the incident location and alternative routes. The volumes with different demands and incident levels, resulting from DTA modeling are imported to a microscopic simulation model for more detailed analysis of dynamic signal control. The microscopic model shows that the implementation of special signal plans during incidents and different demand levels can improve mobility measures

Estimación de impactos de incidentes en el tiempo de viaje en la calle urbana en el caso de super saturación en las luces de traffic

Dynamic signal control strategies are effective in relieving congestions during nontypical days, such as those with high demands, incidents with different attributes, and adverse weather conditions. This research recognizes the need to model the impacts of dynamic signal controls for different days representing, different demand and incident levels. Methods are identified to calibrate the utilized tools for the patterns during different days based on demands and incident conditions utilizing combinations of real-world data with different levels of details. A significant challenge addressed in this study is to ensure that the mesoscopic simulation-based dynamic traffic assignment (DTA) models produces turning movement volumes at signalized intersections with sufficient accuracy for the purpose of the analysis. A new model is developed to estimate the drop in capacity at the incident location by considering the downstream signal control queue spillback effects. The developed capacity reduction models were used to estimate delay due to an urban street incident. The delay was calculated as a combination of the delay due to queuing on the incident link and the increase in upstream intersection control delays due the reduction in maximum throughputs resulting from queue spillback to the upstream intersection The HCS-based method estimated a reduction in delay resulting from the new signal timing plan to be around 3,404 vehicle-hours, whereas the VISSIM shows that the new signal timing saving in delay is 4,008 vehicle-hours. This confirms that the developed method and VISSIM estimation of the benefits are consistent.Las estrategias de control dinámico de la señal son efectivas para aliviar las congestiones durante los días no típicos, como aquellos con altas demandas, incidentes con diferentes atributos y condiciones climáticas adversas. Esta investigación reconoce la necesidad de modelar los impactos de los controles de señales dinámicas para diferentes días que representan diferentes niveles de demanda e incidentes. Los métodos se identifican para calibrar las herramientas utilizadas para los patrones durante diferentes días en función de las demandas y las condiciones del incidente utilizando combinaciones de datos del mundo real con diferentes niveles de detalles. Un desafío importante abordado en este estudio es garantizar que los modelos de asignación dinámica de tráfico (DTA) basados ​​en simulación mesoscópica produzcan volúmenes de movimiento de giro en intersecciones señalizadas con suficiente precisión para el propósito del análisis. Se desarrolla un nuevo modelo para estimar la caída de la capacidad en la ubicación del incidente considerando los efectos de derrame de la cola de control de señal aguas abajo. Los modelos de reducción de capacidad desarrollados se utilizaron para estimar el retraso debido a un incidente en una calle urbana. El retraso se calculó como una combinación del retraso debido a las colas en el enlace incidente y el aumento de los retrasos en el control de la intersección aguas arriba debido a la reducción en los rendimientos máximos resultantes del derrame de la cola a la intersección aguas arriba El método basado en HCS estimó una reducción en el retraso resultante del nuevo plan de temporización de la señal será de alrededor de 3.404 horas de vehículo, mientras que el VISSIM muestra que el nuevo ahorro de temporización de la señal con retraso es de 4.008 horas de vehículo. Esto confirma que el método desarrollado y la estimación VISSIM de los beneficios son consistentes

New Framework and Decision Support Tool to Warrant Detour Operations During Freeway Corridor Incident Management

As reported in the literature, the mobility and reliability of the highway systems in the United States have been significantly undermined by traffic delays on freeway corridors due to non-recurrent traffic congestion. Many of those delays are caused by the reduced capacity and overwhelming demand on critical metropolitan corridors coupled with long incident durations. In most scenarios, if proper detour strategies could be implemented in time, motorists could circumvent the congested segments by detouring through parallel arterials, which will significantly improve the mobility of all vehicles in the corridor system. Nevertheless, prior to implementation of any detour strategy, traffic managers need a set of well-justified warrants, as implementing detour operations usually demand substantial amount of resources and manpower. To contend with the aforementioned issues, this study is focused on developing a new multi-criteria framework along with an advanced and computation-friendly tool for traffic managers to decide whether or not and when to implement corridor detour operations. The expected contributions of this study are: * Proposing a well-calibrated corridor simulation network and a comprehensive set of experimental scenarios to take into account many potential affecting factors on traffic manager\u27s decision making process and ensure the effectiveness of the proposed detour warrant tool; * Developing detour decision models, including a two-choice model and a multi-choice model, based on generated optima detour traffic flow rates for each scenario from a diversion control model to allow responsible traffic managers to make best detour decisions during real-time incident management; and * Estimating the resulting benefits for comparison with the operational costs using the output from the diversion control model to further validate the developed detour decision model from the overall societal perspective

Computational Intelligence in Highway Management: A Review

Highway management systems are used to improve safety and driving comfort on highways by using control strategies and providing information and warnings to drivers. They use several strategies starting from speed and lane management, through incident detection and warning systems, ramp metering, weather information up to, for example, informing drivers about alternative roads. This paper provides a review of the existing approaches to highway management systems, particularly speed harmonization and ramp metering. It is focused only on modern and advanced approaches, such as soft computing, multi-agent methods and their interconnection. Its objective is to provide guidance in the wide field of highway management and to point out the most relevant recent activities which demonstrate that development in the field of highway management is still important and that the existing research exhibits potential for further enhancement

Methods for Utilizing Connected Vehicle Data in Support of Traffic Bottleneck Management

The decision to select the best Intelligent Transportation System (ITS) technologies from available options has always been a challenging task. The availability of connected vehicle/automated vehicle (CV/AV) technologies in the near future is expected to add to the complexity of the ITS investment decision-making process. The goal of this research is to develop a multi-criteria decision-making analysis (MCDA) framework to support traffic agencies’ decision-making process with consideration of CV/AV technologies. The decision to select between technology alternatives is based on identified performance measures and criteria, and constraints associated with each technology. Methods inspired by the literature were developed for incident/bottleneck detection and back-of-queue (BOQ) estimation and warning based on connected vehicle (CV) technologies. The mobility benefits of incident/bottleneck detection with different technologies were assessed using microscopic simulation. The performance of technology alternatives was assessed using simulated CV and traffic detector data in a microscopic simulation environment to be used in the proposed MCDA method for the purpose of alternative selection. In addition to assessing performance measures, there are a number of constraints and risks that need to be assessed in the alternative selection process. Traditional alternative analyses based on deterministic return on investment analysis are unable to capture the risks and uncertainties associated with the investment problem. This research utilizes a combination of a stochastic return on investment and a multi-criteria decision analysis method referred to as the Analytical Hierarchy Process (AHP) to select between ITS deployment alternatives considering emerging technologies. The approach is applied to an ITS investment case study to support freeway bottleneck management. The results of this dissertation indicate that utilizing CV data for freeway segments is significantly more cost-effective than using point detectors in detecting incidents and providing travel time estimates one year after CV technology becomes mandatory for all new vehicles and for corridors with moderate to heavy traffic. However, for corridors with light, there is a probability of CV deployment not being effective in the first few years due to low measurement reliability of travel times and high latency of incident detection, associated with smaller sample sizes of the collected data